Large Universe Revocable Fine-Grained Encryption with Public Auditing

  • Xuewei YanEmail author
  • Hua Ma
  • Zhenhua Liu
  • Ting Peng
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 2)


Attribute-based encryption (ABE) allows for scalable and fine-grained data sharing in a cloud computing environment. However, most of existing ABE schemes with user revocation are not satisfactory on the efficiency side. In addition, since the data are stored on remote servers in the cloud storage environment, data owners do not know whether data is integrated in a timely manner. In this paper, we propose a novel large universe revocable fine-grained encryption with public audit- ing (LRA-FE) scheme based on prime-order bilinear groups. In this construction, we utilize extended proxy-assisted approach and appending redundancy approach, which weakens the trust of the cloud server. Furthermore, the proposed system in- troduces an auditor to inspect the integrity of data stored in the cloud. The size of attribute space can be exponentially large because our construction supports large u- niverse. After comprehensive comparisons with the state-of-the-art works, the LRA- FE scheme features lightweight computation at the user side such that users can use resource-constrained devices to access cloud data.


Attribute-Based Encryption Large Universe Revocation Audit 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bethencourt, J., Sahai, A., Waters, B.: Ciphertext-policy attribute-based encryption. In: Proceedings of IEEE S and P, pp. 321-334, 2007Google Scholar
  2. 2.
    Lewko A, Waters B.: Unbounded HIBE and attribute-based encryption. Advances in Cryptology-EUROCRYPT 2011. Springer Berlin Heidelberg, PP. 547-567, 2011.Google Scholar
  3. 3.
    Liang, K., Liu, J.K., Wong, D.S., Susilo, W.: GO-ABE: an efficient cloud-based revocable identity-based proxy re-encryption scheme for public clouds data sharing. In: Proceedings of ESORICS 2014, pp. 257-272, 2014.Google Scholar
  4. 4.
    Ma H, Zhang R,Wan Z, et al.: Verifiable and Exculpable Outsourced Attribute-Based Encryption for Access Control in Cloud Computing. IEEE Transactions on Dependable and Secure Computing. DOI 10.1109/TDSC.2015.2499755.Google Scholar
  5. 5.
    Rouselakis Y, Waters B.: Practical constructions and new proof methods for large universe attribute-based encryption. Proceedings of the 2013 ACM SIGSAC conference on Computer and communications security. ACM, pp. 463-474, 2013.Google Scholar
  6. 6.
    Sahai A, Waters B.: Fuzzy identity-based encryption. Advances in Cryptology-EUROCRYPT 2005. Springer Berlin Heidelberg, pp. 457-473, 2005.Google Scholar
  7. 7.
    Yang G, Yu J, Shen W, et al.: Enabling public auditing for shared data in cloud storage supporting identity privacy and traceability. Journal of Systems and Software, 113: pp. 130-139, 2016.Google Scholar
  8. 8.
    Yang J J, Li J Q, Niu Y.: A hybrid solution for privacy preserving medical data sharing in the cloud environment. Future Generation Computer Systems, 43: pp. 74-86, 2015.Google Scholar
  9. 9.
    Yang, Y., Lu, H., Weng, J., Zhang, Y., Sakurai, K.: Fine-grained conditional proxy reencryption and application. In: Chow, S.S.M., Liu, J.K., Hui, L.C.K., Yiu, S.M.(eds.) ProvSec 2014. LNCS, vol. 8782, pp. 206-222. Springer, Heidelberg 2014. Extended version to appear: Pervasive and Mobile Computing, ELSEVIERGoogle Scholar
  10. 10.
    Yang Y, Liu J K, Liang K, et al: Extended Proxy-Assisted Approach: Achieving Revocable Fine-Grained Encryption of Cloud Data. Computer Security-ESORICS 2015. Springer International Publishing pp. 146-166, 2015.Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.School of Mathematics and StatisticsXidian UniversityXi’anP.R. China
  2. 2.StateKey Laboratory of Information Security (Institute of Information Engineering)Chinese Academy of SciencesBeijingChina

Personalised recommendations